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How do informal lending institutions affect entrepreneurship? This paper aims to investigates the role of formal and informal credit market institutions in the decision to become an entrepreneur over the life cycle.

The author developed a dynamic Roy model in which a decision to become an entrepreneur depends on the access to formal and informal credit markets, nonpecuniary benefits of entrepreneurship, career-specific entry costs, prior work experience, education, unobserved abilities and other labor market opportunities (salaried employment and nonemployment). Using detailed Russian panel microdata (the Russia longitudinal monitoring survey) and estimating a structural model of labor market decisions and borrowing options, the author assesses the impact of the development of informal and formal credit institutions.

The expansion of traditional (formal) credit market institutions positively impacts all workers’ categories, reduces the share of entrepreneurs who borrow from informal sources and incentivizes low-type entrepreneurs to switch to salaried employment. The development of the informal credit market reduces the percentage of high-type entrepreneurs who borrow from formal sources. In the case of default, a higher value of the social network or higher costs of losing social ties demotivate low-type entrepreneurs to borrow from informal sources. The author highlights the practical implications of estimates by evaluating policies designed to promote entrepreneurship, such as subsidies and accessibility regulations in credit market institutions.

This study contributes to the literature in several ways. Unlike other studies that focus on individual characteristics in the selection for self-employment [Humphries (2017), Hincapíe (2020), Gendron-Carrier (2021), Dillon and Stanton (2017)], the paper models labor and borrowing decisions jointly. Previous studies discuss transitions between salaried employment and self-employment, taking into account entrepreneurial earnings, wealth, education and age, but do not consider the availability of financial institutions as a driving factor for the selection into self-employment. To the best of the author’s knowledge, this paper shows for the first time that the transition from salaried employment to self-employment is standard and consistent with changes in access to financial institutions. Another feature of this study is incorporating both types of credit markets – formal and informal. The survey by the European Central Bank on the Access to Finance of Enterprises (2018) shows 18% of small and medium enterprise in EU pointed funds from family or friends. Therefore, the exclusion from consideration of informal credit markets may distort the understanding of the role of the accessibility of credit markets.

The purpose of this study was to examine racial/ethnic differences in AFS use and their contributing factors using a decomposition analysis.

The 2018 National Financial Capability Study dataset was used to analyze the four major types of AFS—title loans, payday loans, pawnshops, and rent-to-own (RTO) stores—as proxies for AFS use. The study conducted both logistic regression analysis and decomposition analysis to examine the contributing factors.

The results of the logistic regression analysis demonstrated significant disparities in the use of alternative financial services (AFS) among racial and ethnic groups. Specifically, it was found that Blacks were more likely to utilize title and payday loans, pawnshops, and rent-to-own (RTO) stores compared to Whites. In contrast, Hispanics and Asians/individuals of other ethnicities were less likely to use title loans, but Hispanics were more likely to opt for payday loans over Whites. Furthermore, objective financial literacy exhibited a negative association with the likelihood of using these four types of AFS, whereas subjective financial literacy consistently showed a positive association. When examining the decomposition analyses, it became evident that both objective and subjective financial literacy played significant roles in explaining the racial and ethnic disparities in AFS usage. However, the patterns varied in three specific pairwise comparisons.

This study revealed the relative contributions of each factor to the racial/ethnic disparities through decomposition analysis. Our Fairlie decomposition approach addressed non-linearities within the decomposition framework, particularly in estimating the probabilities of AFS utilization, given its binary outcomes. This extension builds upon the Oaxaca decomposition. The study offers valuable insights into the variations in AFS use among different racial and ethnic groups.

This study aims to evaluate the information behavior of the Banarasi Sarees weaving community and propose an information-focused policy tailored to their needs.

This study was conducted in seven weaver-centered areas in Varanasi and was designed around semi-structured interviews to explore various information-related aspects among the weavers. It aims to focus on their knowledge of weaving, their information needs, seeking behavior, preferred communication channels, prioritization of information and methods for enhancing information-related situations.

It was found that a lack of information among weavers significantly impacts their livelihoods and businesses. They struggle to make product, pricing and marketing decisions without access to accurate, timely and relevant information. They cannot expand their businesses and invest in new equipment and materials. The weavers need a library with a specialized collection and a qualified librarian to guide them in using the information sources. They also need a dedicated information system and community information centers to provide better information services.

This study is a work whose expected results and findings would help policymakers adopt measures to encourage providing information services through public libraries and community information centers. The results of this study may be further used to frame information policy for weavers and other occupational communities.

In this article, the research objective is to empirically investigate the effect of the adoption of the Brazilian instant payment system, Pix, on the local credit market structure and the diversification of the banking system in Brazilian municipalities.

By analyzing the data, in this study, we compile and align data from supervisory and public sources, covering the period from 2019 to 2022 in Brazil. As of 2014, Brazil was comprised of 5568 municipalities distributed across five regions: North (450 municipalities), Northeast (1792), Midwest (467), Southeast (1668) and South (1191), according to the Brazilian Institute of Geography and Statistics (IBGE). Our analysis relies on the volume and quantity of Pix to the outstanding credit operations in Brazil.

This article provides evidence that the widespread adoption of Pix has impacted the financial structure of municipalities. This analysis of banking concentration in the country and municipalities, based on banking relationships, helped us assess whether the adoption of Pix had any correlation with the increase in credit lines. Overall, the results from the statistical tables suggest that the adoption of Pix may be having a positive impact on the local credit market structure.

The originality contribution of the study is to initiate an investigation into the impact of this instant payment system, Pix, on the Brazilian reality. Pix was launched in 2020, amid the COVID-19 pandemic, and had significant numbers, such as over 61% of the adult population having at least one Pix key registered in a little over a year; about 100 million people made at least one payment with Pix; and more than 1.4 billion transactions per month, with 72% between individuals, as presented by the REB 2021.

The present study examines the determinants of households’ access to agricultural credit through institutional and non-institutional sources. The study evaluates the role of gender of the borrowers in accessing credit in rural India. Further, the paper also studies the impact of institutional variables in determining rural households’ access to credit.

The study used a multinomial logit model to identify the different factors that determine a farmer’s access to different credit sources.

The study reveals that substantial proportions of rural households do not access credit through any of the sources and the situation is very grim for the female-headed households (FHHs). The study highlights the importance of demographic, farm and institutional variables in determining households’ access to credit. Institutional variables significantly enhance rural credit access but favor male-headed households (MHHs). It highlights the need for policy intervention to target the specific needs of female borrowers. Further, the study also highlights the importance of adequate credit policy measures to address farmers’ vulnerability to natural disasters, mainly droughts.

The results of the study are based on recent unit-level data from the 77th Round of the National Sample Survey Organization (NSSO) survey. The survey covers a large number of farm households and reports information for the year 2018–2019.

The peer review history for this article is available at https://publons.com/publon/10.1108/IJSE-08-2022-0552

The current approach to valuing customers is based on the notion of discounted profit generated by the customers over the lifetime of the relationship, also known as customer lifetime value (CLV). However, in the financial services industry, the customers who contribute the most to the profitability of a firm are also the riskiest customers. If the riskiness of a customer is not considered, firms will overestimate the true value of that customer. This paper proposes a methodology to adjust CLV for different types of risk factors and creates a comprehensive measure of risk-adjusted lifetime value (RALTV).

Using data from a major credit card company, we develop a measure of risk adjusted lifetime value (RALTV) that accounts for diverse types of customer risks. The model is estimated using Stochastic Frontier Analysis (SFA).

Major findings indicate that rewards cardholders and affinity cardholders tend to score higher within the RALTV framework than non-rewards cardholders and non-affinity cardholders, respectively. Among the four different modes of acquisition, the Internet generates the highest RALTV, followed by direct mail.

This paper not only controls for different types of consumer risks in the financial industry and creates a comprehensive risk-adjusted lifetime value (RALTV) model but also shows empirically the value of using RALTV over CLV for predicting future performance of a set of customers. Further, we investigate the impact of a firm’s acquisition and retention strategies on RALTV. The measure of risk-adjusted lifetime value is invaluable for managers in financial services.

This study aims to present an innovative predictive methodology that transitions from traditional efficiency assessment techniques to a forward-looking strategy for evaluating working capital management(WCM) and its determinants by integrating data envelopment analysis (DEA) with artificial neural networks (ANN).

A slack-based measure (SBM) within DEA was used to evaluate the WCME of 1,388 firms in the Indian manufacturing sector across nine industries over the period from April 2009 to March 2024. Subsequently, a fixed-effects model was used to determine the relationships between selected determinants and WCME. Moreover, the multi-layer perceptron method was applied to calculate the artificial neural network (ANN). Finally, sensitivity analysis was conducted to determine the relative significance of key predictors on WCME.

Manufacturing firms consistently operate at around 50% WCME throughout the study period. Furthermore, among the selected variables, ability to create internal resources, leverage, growth, total fixed assets and productivity are relatively significant vital predictors influencing WCME.

The integration of SBM-DEA and ANN represents the primary contribution of this research, introducing a novel approach to efficiency assessment. Unlike traditional models, the SBM-DEA model offers unit invariance and monotonicity for slacks, allowing it to handle zero and negative data, which overcomes the limitations of previous DEA models. This innovation leads to more accurate efficiency scores, enabling robust analysis. Furthermore, applying neural networks provides predictive insights by identifying critical predictors for WCME, equipping firms to address WCM challenges proactively.

This study aims to examine the impact of financial inclusion and bank stability on agricultural productivity in Sub-Saharan Africa (SSA).

The study used 38 countries in the SSA with data spanning between 2004 and 2021. The data were analyzed using the two-step system generalized method of moments (GMM) and the panel-corrected standard error (PCSE) model.

The study found a positive effect of financial inclusion and bank stability on agricultural productivity. The study also discovered that while the access component of financial inclusion has a negative influence on agricultural productivity, the usage dimension has a positive impact.

The study suggests to policymakers that an inclusive and stable financial system improves agricultural productivity. The findings recommend that policymakers should empower farmers to leverage financial inclusion.

This study provides insightful discussion on the impact of financial inclusion and its various dimensions and bank stability on agricultural productivity in SSA.

This paper aims to examine the alternative financing available for sustainable infrastructure development in Nigeria’s sub-nations. Specifically, the study question is: what financial vehicles do sub-nations seek most, and what are the underlying reasons for their preferences?

The study used a two-round Delphi method, using a questionnaire to gather data from high-ranking government officials in states that have localised sustainable development projects in Nigeria.

Results show that fundamental to sub-national sustainable infrastructure projects are federal allocations, pension funds, private equity, bonds and concessionary grants. Sub-nationals prefer these options, especially the emphasis on private equity, and the concessional funding through catalytic or blended finance because of their relatively lower or below-market interest rates.

The practical significance of this study is that the state’s policymakers can now identify appropriate strategies that enhance the shift towards these sustainable financing options, which will serve as a key catalyst in their 2030 and beyond vision to accelerate their state's infrastructure climate complaint. Equally, investors possessing funds with such attributes will gain an understanding of a prospective market within Nigeria’s sub-nation.

This study aims to improve the development of sustainable infrastructure in Nigeria’s sub-nations, which would have a beneficial effect on society by mitigating the effects of climate change.

The recommendations of this study can contribute to the development of innovative financial models for sub-national infrastructure development, thereby reducing reliance on revenue generated from fossil fuels.

People with disabilities (PwDs) encounter several impediments to employment prospects, contributing to India's huge employment gap. Entrepreneurship offers a different avenue for PwDs to overcome these constraints. Entrepreneurship Support Organizations (ESOs) play a significant role in assisting PwD entrepreneurs. The present study aims to explore challenges encountered by entrepreneurs with disabilities (EwDs) in starting or sustaining a business in an Indian ecosystem. The study further aims to examine the status of entrepreneurial outcomes while comprehending the intersection of the challenges of disability and entrepreneurship. The study draws on stakeholder and social identity theories to understand this critical connection.

A qualitative approach is applied to study the phenomenon. Semi-structured interviews were conducted with 13 EWDs and 5 ESOs to explore the challenges faced and the available support in the Indian context. The study explores the level of coordination and roles these organizations play in fostering an entrepreneurial culture for PWDs.

The research findings explore novel challenges and facilitators of entrepreneurial pursuits of EwDs. The study further offers implications for policymakers to foster inclusive infrastructure, financial institutions to provide accessible credit options, and ESOs to amplify tailored assistance. Importantly, these dynamics have implications for advancing relevant Sustainable Development Goals.

The intersectional lens of disability and entrepreneurial challenges offered to study PwD entrepreneurship highlights new directions for exploring the phenomenon in deeper detail. Further, the theoretical underpinnings of stakeholder and social identity theories provide practical and indispensable insights into the phenomenon.